Software Engineers, AI Security

Saviynt•El Segundo, CA

70d

About The Position

Saviynt is an identity platform built to power and protect the world at work. With the rise of AI and Agents, the identity perimeter needs to be secured at scale. Come join as founding members of Saviyntâs AI Security team and enable us to build out AI security for the world's leading enterprises. In a world of digital transformation, where organizations are faced with increasing cyber risk but cannot afford defensive measures to slow down progress, Saviyntâs Enterprise Identity Cloud gives customers unparalleled visibility, control and intelligence to better defend against threats while empowering users with right-time, right-level access to the digital technologies and tools they need to do their best work.

Requirements

10+ years of software engineering experience
Expert-level ability utilizing technologies such as Java, Spring Framework, REST and Microservices
Familiar with AI tools and curious about MCP, A2A, Agentic frameworks. Have a continuous learning mindset and not hesitate to venture into unchartered territory
Ability to perform research and go deep into platforms is a strong plus
Strong Experience as a Java Engineer developing applications based on Security principles, cloud platforms (AWS, Azure, or Google Cloud) and Containerization (Docker, Kubernetes)
Deep understanding of data structures, algorithms, and design patterns
Hands on experience with SQL, ElasticSearch, Redis, CI/CD, AWS Glue, Kafka
Experience in increasing levels of responsibility managing application development, solution architecture, design and delivery, and process improvement
Experience with unit, functional and system integration testing
Extensive understanding of working in an agile environment utilizing Scrum and Kanban
Experience with Git (GitHub/GitLab), automatic deployments, continuous integration
Hands on experience using IntelliJ or Eclipse/My Eclipse IDE, writing Junit test cases, working with Maven/Ant
Experience with AI development tools in SDLC such as Amazon Q, Github Copilot, Cursor, and similar productivity assistants
Familiarity with various architectural patterns (e.g., event-driven, microservices, serverless) and their trade-offs

Responsibilities

Design, implement, test and release e2e workflows for our AI security product.
Work across multiple agent platforms like AWS Bedrock, Google AgentSpace, Salesforce AgentForce , building foundational solutions, using cloud, SAAS and AI design patterns and technologies.
Use AI and Agents to secure AI, using CUA agents, various LLMâs , agentic frameworks like ADK, Langchain among others.
Design and develop secure, scalable, multi-tenant software solutions that run seamlessly across major cloud platforms like AWS and Azure.
Act as a technical expert and thought leader, influencing product direction and engineering best practices.
Drive continuous improvement in engineering processes, tooling, and operational reliability.
Collaborate with internal teams to produce software design and architecture
Test and deploy applications and systems.
Revise, update, refactor and debug code.
Ability to start a program from scratch as well as maintain existing services.
Develop documentation throughout the software development life cycle.
Serve as an expert on applications and provide technical support.